DocumentCode
1695134
Title
A SIFT-Kalman information fusion tracking algorithm based on PCA
Author
Zhou Kai ; Fan Rui-xia ; Li Wei-xing
Author_Institution
Sch. of Autom., Beijing Inst. of Technol., Beijing, China
fYear
2010
Firstpage
6084
Lastpage
6088
Abstract
In order to ensure the accuracy of vehicle tracking in the situation of similar background, the SIFT algorithm is proposed. Meanwhile, the PCA algorithm is used to reduce the dimensionality of SIFT descriptors to improve the system´s real-time and a SIFT-Kalman information fusion tracking algorithm based on PCA is set up. The results of experiments showed the proposed algorithm performs well when the object is cluttered.
Keywords
Kalman filters; image fusion; optical tracking; principal component analysis; road vehicles; traffic engineering computing; PCA algorithm; SIFT algorithm; SIFT descriptor; SIFT-Kalman information fusion tracking; principal component analysis; vehicle tracking; Computer vision; Conferences; Educational institutions; Kalman filters; Pattern recognition; Principal component analysis; Vehicles; Kalman Filter; PCA; SIFT; Vehicle Tracking;
fLanguage
English
Publisher
ieee
Conference_Titel
Intelligent Control and Automation (WCICA), 2010 8th World Congress on
Conference_Location
Jinan
Print_ISBN
978-1-4244-6712-9
Type
conf
DOI
10.1109/WCICA.2010.5554734
Filename
5554734
Link To Document